PROJECT SUMMARY The purpose of this study is to examine how access to dental care among low-income adults is impacted by state Medicaid policies regarding eligibility, dental coverage, cost-sharing and dentist reimbursement. Oral health is integral to overall health, economic productivity and well-being. Yet access to dental care continues to be a major public health problem for low-income adults, leading to untreated disease, pain, poor systemic health and substantial economic burden. In recent years, several policy changes under the Affordable Care Act (ACA) such as Medicaid expansion and dependent care coverage could significantly impact access to dental care among the poor non-elderly adults. In addition, there is extensive cross-state variation in terms of dental benefits covered for Medicaid adults. These variations provide natural experiments to examine the effect of Medicaid policies on access to dental care. Moreover, under the current health reform discussions, state Medicaid programs are anticipated to gain autonomy in resource allocation, yet may receive significantly less federal funding, making the need for robust evidence on relative effectiveness of Medicaid policy alternatives available to the states paramount. The overarching goal of this application is to advance the research career of the candidate (Dr. Singhal) by protecting her time for training and research on these critical issues in oral health policy. This goal will be accomplished through additional training in complementary disciplines of econometrics and machine learning, and their application to estimate the impacts of Medicaid coverage and payment generosities on access to dental care. The project brings together complementary secondary data from multiple sources including: large national survey data (National Health Interview Survey), administrative enrollment and claims data (Medicaid Analytic eXtract) and linked survey and claims data. Leveraging these data and training resources, this project will: 1) develop synthetic indices of Medicaid dental coverage and payment generosities; 2) estimate the effect of each policy alternative and combined generosity indices on various measures of access to dental care; and 3) predict the relative effectiveness of policy alternatives and their combinations on access to dental care. We will use econometric methods including instrumental variables, difference-in-difference and regression discontinuity models to develop the generosity indices and to estimate the impact of Medicaid generosity. To develop and validate the predictive model, we will use supervised machine learning approaches (e.g. decision tree learning) using linked survey and claims data. The results will provide evidence needed to inform future strategies to ensure efficient use of health care resources to reduce oral health disparities. The completion of this project will also enable Dr. Singhal to establish a research program as an independent research investigator with support from her multi-disciplinary mentoring and advising teams and the vibrant research community at Boston University.